KR20110043338A - Apparatus and method for detecting signal in spatial multiplexing system - Google Patents

Abstract

PURPOSE: A signal detecting device and method thereof are provided not to generate an error performance difference when signal detecting of a data stream. CONSTITUTION: A part linear coefficient generating unit(300) generates linear weight matrix by using a preset algorithm in a channel matrix which is formed between a transmission unit and a signal receiving unit. A part symbol removing unit(302) generates a first symbol vector by removing all symbols available for transmission of each transmission antenna in a received total data stream. The part symbol detecting unit(304) generates a transmission symbol candidate vector by using the generated linear weight matrix and the first symbol vector.

Description

Apparatus and Method for detecting signal in spatial multiplexing system

The present invention relates to an apparatus and a method for detecting a signal in a spatial multiplexing system. More particularly, the present invention relates to a signal detecting apparatus and a method of receiving a plurality of antennas in a single receiver having a plurality of antennas. The present invention relates to a signal detection apparatus and a method in which error performance difference does not significantly occur.

Efforts are being made to apply MIMO (Multi Input Multi Output) technology to the system to maximize spectrum efficiency and transmission speed in wireless communication systems. Recently, MIMO techniques, which are only mentioned by theory, have been applied to real systems, and there are many cases of improving system performance. MIMO technology has been adopted in the recently commercialized IEEE 802.16e mobile-WiMAX system, LTE system represented by 4G technology, IEEE 802.16m system. However, it is difficult to use MIMO technology in the uplink of a mobile terminal because MIMO technology has multiple transmitter antennas and is difficult to apply when the transmission power is small.

Recently, a cooperative spatial multiplexing scheme that achieves MIMO effect by operating multiple transmitters having one antenna or two antennas as if one transmitter uses multiple antennas by applying the MIMO transmission scheme is WiMAX, LTE, and IEEE 802.16. Adopted for uplink of m.

Collaborative Spatial Multiplexing (CSM) is a technique for transmitting data simultaneously by allocating the same frequency resource when a plurality of terminals each have one or more transmitting antennas in a multi-user uplink system.

An advantage of the cooperative spatial multiplexing scheme is that the number of antennas can be reduced compared to MIMO terminals while improving the transmission efficiency of the system, thereby reducing the complexity and reducing the manufacturing cost of the terminals. In addition, when a cooperative spatial multiplexing scheme is used in an uplink of a multi-user MIMO system, each user has an independent modulation and coding scheme (MCS) level. Modulation and coding (AMC) is performed. Through this process, similar error performance is guaranteed between users.

As described above, in the multi-user system, the cooperative spatial multiplexing method can increase the transmission efficiency by transmitting data streams of a plurality of users to the same resource. Separating the spatially multiplexed signal is essential.

Since the cooperative spatial multiplexing method operates multiple transmitters as if one transmitter uses multiple antennas, the signal detection technique of the existing spatial multiplexing MIMO system can be considered. Signal detection techniques of the MIMO system receiver using spatial multiplexing can be classified into linear signal detection, nonlinear signal detection, sub-optimal signal detection, and optimal signal detection.

Zero-Forcing (ZF) and Minimum Mean Square Error (MMSE) signal detection methods, which belong to the linear signal detection method, can be implemented in a relatively simple structure due to their low computational complexity, but have significantly degraded performance compared to that of the optimal signal detection method. see. The OSIC (Ordered Successive Interference Cancellation) signal detection technique, which is a nonlinear signal detection technique, is a technique for reducing the influence of an interference signal by sequentially removing signals detected according to a predetermined detection order.

The OSIC signal detection technique has more computational complexity than the linear signal detection technique, but shows higher performance than the linear signal detection technique. However, the performance is significantly degraded compared to the optimal signal detection technique that shows the best performance. The maximum likelihood (ML) signal detection method that shows the best performance detects the signal by selecting the least square Euclidean distance by calculating and comparing the squared Euclidean distance by substituting all candidate vector values of the transmittable signal. to be. Therefore, as the number of transmitted data streams and the modulation order increase, the computational complexity increases exponentially, and has a very high computational complexity. The signal detection technique which has high performance complexity similar to the optimal performance while reducing the high computational complexity of the ML signal detection technique includes QRM-MLD (maximum likelihood detection with QR decomposition, sphere decoding). The SD method calculates the squared Euclidean distance by substituting the symbols of constellations within a limited distance, and the average complexity can be significantly lower than the ML method. However, since the depth-first search method, the maximum complexity cannot be predicted. There is a difficulty.

QSD-MLD, unlike SD, is a breadth-first search method with a fixed maximum complexity. When the number of candidate vectors is sufficient, the performance is almost the same as that of the ML signal detection technique, but when the number of candidate vectors is small, the performance decreases significantly.

Among the existing signal detection methods described above, the non-linear detection method of the OSIC series and the suboptimal signal detection methods such as QRM-MLD and SD may cause error propagation problems, restriction of substitution symbols, or limitation of symbol candidate vectors in the signal detection process. Performance differences occur between data streams. In the case of the signal detection technique of the OSIC series, an error propagation problem occurs when a previously detected symbol is incorrectly detected in the process of sequentially detecting signals. Therefore, there is a difference in signal detection performance between data streams. In the case of SD and QRM-MLD, a symbol that can be transmitted is limited to a data stream in the process of detecting a signal, and a square Euclidean distance is generated using only candidate symbols. Therefore, in the case of SD and QRM-MLD as in the OSIC method, there is a difference in signal detection performance between data streams. The signal detection technique that generates such a phenomenon is not suitable for applying to cooperative spatial multiplexing. As described above, in the uplink of a multi-user MIMO system using a cooperative spatial multiplexing scheme, the error performance of each user is set to be similar in consideration of the user's channel environment and QoS, and a large difference in signal detection performance between data streams is obtained. If you use the existing signal detection technique that generates, the setting of the existing MCS level becomes useless. Therefore, in the signal detection process, the suboptimal signal detection techniques such as QRM-MLD, SD, and non-linear detector methods that affect the error performance between data streams due to the error propagation problem and the constraints of the signal detection algorithm are collaborative space multiplexing. It is not suitable for multi-user MIMO systems using the scheme.

In order to solve the above problems of the prior art, the present invention provides a plurality of antennas when a data stream is transmitted through a spatial multiplexing scheme in a single transmitter having a plurality of antennas or a plurality of transmitters having at least one antenna. The present invention proposes a signal detection apparatus and method in a spatial multiplexing system in which a error performance difference does not significantly occur when a signal of a data stream is detected by a receiving unit having a signal receiver.

Another object of the present invention is to provide an apparatus and method for detecting a signal in a spatial multiplexing system having a similar performance to that of the ML signal detection technique, which is an optimal signal detection technique in a hard decision or a soft decision, without having a large complexity. It is.

It is still another object of the present invention to provide an apparatus and method for detecting signals in a spatial multiplexing system having similar error performance between different data streams.

According to a preferred embodiment of the present invention to achieve the above object, a signal detection device of a single receiver having a plurality of antennas in a system in which at least one transmitter transmits a data stream in a spatial multiplexing scheme, the at least one A partial linear coefficient generator for generating a linear weight matrix using a predetermined algorithm in a channel matrix formed between the transmitter and the single receiver; A partial symbol remover configured to remove all transmittable symbols of each transmit antenna from the received total data streams to generate a first symbol vector; And a partial symbol detector configured to generate a transmission symbol candidate vector using the generated linear weight matrix and the first symbol vector.

According to another aspect of the present invention, a signal detection device of a single receiver having a plurality of antennas in a system in which at least one transmitter transmits a data stream in a spatial multiplexing scheme,

And a partial symbol remover for generating a symbol vector from which all transmittable symbols of each transmit antenna are removed from the entire received data stream, wherein the partial symbol remover selects a transmittable symbol of an i th transmit antenna and selects the selected symbol. Provided is a signal detection apparatus for generating the symbol vector by multiplying a column matrix corresponding to the i < th > transmit antenna of the channel matrix and then removing the multiplied value from the entire data stream.

According to another aspect of the present invention, a method in which a single receiver having a plurality of antennas detects a signal in a system in which at least one transmitter transmits a data stream in a spatial multiplexing scheme, the method comprising: (a) at least one transmitter and Generating a linear weight matrix using a preset algorithm in a channel matrix formed between the single receivers; (b) generating a first symbol vector by removing all transmittable symbols of each transmit antenna from the received total data stream; (c) generating a transmission symbol candidate vector using the generated linear weight matrix and the first symbol vector; And (d) calculating a square Euclidean distance using the generated transmission symbol candidate vector.

According to the present invention, the partial symbol elimination unit applies the partial symbol elimination process once for all data streams and the partial symbol detection unit for each data stream has the advantage that the error performance difference between all data streams is similar. .

As the invention allows for various changes and numerous embodiments, particular embodiments will be illustrated in the drawings and described in detail in the written description. However, this is not intended to limit the present invention to specific embodiments, it should be understood to include all modifications, equivalents, and substitutes included in the spirit and scope of the present invention. Like reference numerals are used for like elements in describing each drawing.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art. Terms such as those defined in the commonly used dictionaries should be construed as having meanings consistent with the meanings in the context of the related art and shall not be construed in ideal or excessively formal meanings unless expressly defined in this application. Do not.

 Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In order to facilitate a thorough understanding of the present invention, the same reference numerals are used for the same means regardless of the number of the drawings.

According to the present invention, the total number of antennas of a single transmitter having a plurality of antennas or a plurality of transmitters (for example, a terminal) having at least one antenna is M and the number of antennas is N in a system for transmitting a data stream by spatial multiplexing. It provides a method by which a single receiver (e.g., base station) can detect a signal in an optimal manner.

Particularly, in the multi-user uplink system, multi-user collaborative spatial multiplexing (CSM) for simultaneously transmitting data by allocating the same frequency resource when a plurality of terminals have one or more transmit antennas is used. The present invention can be applied to signal detection in an uplink system. Hereinafter, signal detection in a cooperative spatial multiplexing uplink system will be described.

The cooperative spatial multiplexing system can express mathematically the same as a system including one transmitter having M antennas and one receiver having N antennas for a general MIMO system.

Hereinafter, a system and a conventional signal detection technique to which the present invention is applied will be described with reference to FIGS. 1 and 2.

1 is a block diagram of a transmitting and receiving end of a general MIMO system.

As shown in FIG. 1, a transmitter of a general MIMO system may include a channel encoder 100, an interleaver 102, a spatial multiplexer 104, and a plurality of antennas 106, and the receiver may include a plurality of antennas ( 110, a signal detector 112, a deinterleaver 114, and a channel decoder 116.

The transmitted data stream passes through the channel encoder 100 and the interleaver 102, and then a symbol having a different value is transmitted through each antenna 106 through the spatial multiplexer 104.

On the other hand, each antenna 110 of the receiver receives a radio signal passing through a different channel environment. The signal received as described above is a multiple signal through different channel environments, which are separated by the signal detector 112 after the channel estimation.

In the case of signal detection, if a hard decision is used, bits of each symbol are detected through demodulation of the detected symbol, and in the case of a soft decision, the bit-LRL information of the detected symbol is transmitted to the deinterleaver 114. The channel decoder 116 detects a bit of the hard-determined symbol.

2 is a block diagram of a cooperative spatial multiplexing system.

FIG. 2 illustrates a basic concept of a cooperative spatial multiplexing system in which data streams subjected to channel encoding are transmitted from a plurality of transmitters and receive data streams using a plurality of antennas in one receiver.

In the cooperative spatial multiplexing system, if the total number of transmitter antennas is the same as the number of antennas of the transmitter of the spatial multiplexing MIMO system described in FIG. 1 and the number of antennas of the receiver is the same, the cooperative spatial multiplexing system is the same. The relationship of the signal can be expressed by the equation.

However, in the cooperative spatial multiplexing system, each transmitter includes independent modulators 200-1 to 200-M, which are not spatial multiplexers.

Assuming a spatial multiplexed MIMO system having M transmit antennas and N receive antennas, a relationship between a wireless communication channel and a transmit / receive signal may be represented by Equation 1 as follows.

는

번째 송신안테나로부터 송신된 신호(심볼)를 나타내고,here

Is

Indicates a signal (symbol) transmitted from the first transmission antenna,

는

번째 수신 안테나에서 수신된 신호를 나타내며,

Is

Signal received from the first receive antenna,

는

번째 송신 안테나와

번째 수신 안테나 사이의 채널 이득을 나타낸다.

Is

With the first transmit antenna

The channel gain between the first receiving antenna is shown.

은 환형 대칭 백색 가우시안 잡음이라고 가정한다. 송신 심볼Noise

Is assumed to be an annular symmetric white Gaussian noise. Transmit symbol

는 QAM(Qadrature Amplitude Modulation) 변조된 심볼이라고 가정하고, 수신기에서는 채널 추정을 완벽하게 하여 채널 정보를 알고 있다고 가정한다. 협력적 공간다중화 시스템에서는 송신 심볼이 각기 다른 송신 안테나에서 전송된 심볼이라고 가정한다.

Is assumed to be a QAM (Qadrature Amplitude Modulation) modulated symbol, and it is assumed that the receiver knows the channel information by perfecting the channel estimation. In a cooperative spatial multiplexing system, it is assumed that a transmission symbol is a symbol transmitted from different transmission antennas.

The ML technique for detecting signals with optimal performance calculates the squared Euclidean distance for each of the transmittable vector. For hard decision, the ML method determines the transmitted signal vector corresponding to the minimum value as the transmission symbol. In the soft decision, a bit LLR is generated using a squared Euclidean distance generated by using all transmittable signal vectors, and the symbol is detected by applying the MAP, log-MAP, and max-log-MAP methods. The ML signal detection technique can be expressed by Equation 2 below.

개의 자승 유클리디언 거리를 연산하여야 한다. 이와 같이 ML 신호검출 기법의 연산량은 변조 차수(C)에 송신 안테나수의 지수승으로 증가하기 때문에 실제 시스템에 적용하기 힘들다.When the number of transmit / receive antennas is M and the ML signal is detected by using the above formula

The squared Euclidean distance is calculated. As described above, the amount of computation of the ML signal detection technique increases with the exponential power of the number of transmit antennas in the modulation order C, making it difficult to apply to an actual system.

The ZF and MMSE techniques, which can be implemented with a small amount of computation, use the inverse function of the channel, which causes noise amplification in the ZF technique. The MMSE technique considers the noise amplification phenomenon of the ZF technique and shows a performance improvement over the ZF technique. However, there is a problem that the performance is significantly lower than the optimal performance. The ZF and MMSE techniques can be expressed by Equation 3 below.

Where + stands for linear weight matrix, ^H stands for conjugate prefix matrix,

은 송신전력이 1일 때 잡음의 전력을 나타낸다.

Denotes the power of noise when the transmit power is one.

는

단위행렬을 나타낸다. ZF 기법은 잡음을 고려하지 않고 채널응답의 의사 역행렬을 구하여 간섭신호를 제거시키는 알고리즘이며, MMSE 기법은 잡음까지 고려하여 복조신호가 최대 신호대잡음비를 갖도록 하는 알고리즘이다.Also

Is

Represents a unit matrix. The ZF technique removes interference signals by taking the pseudo inverse of the channel response without considering the noise. The MMSE technique considers the noise to make the demodulated signal have the maximum signal-to-noise ratio.

As described above, ZF and MMSE techniques have been used for the detection of spatially multiplexed signals in MIMO systems, but they show significantly degraded performance compared to ML, which is an optimal signal detection technique that can be implemented with a relatively simple structure.

According to a preferred embodiment of the present invention, a signal detection method is proposed that can exhibit similar performance to the optimal signal detection technique without increasing the complexity.

3 is a block diagram of a signal detection apparatus according to an exemplary embodiment of the present invention.

3 is related to a signal detection device (signal detector 112) included in a cooperative spatial multiplexing system as shown in FIG. 2, and as shown in FIG. 3, the signal detection device according to the present invention includes a partial linear coefficient generator ( 300, the partial symbol remover 302, the partial symbol detector 304, the squared Euclidean distance calculator 306, the bit LLR generator 308, and the least squared Euclidean selector 310 may be included. have.

In the following description, the total number M of antennas of a plurality of transmitters is four, and the number N of antennas of one receiver is four.

In the present invention, the input of the signal detection apparatus is a channel gain value obtained by channel estimation, stream data received at each antenna, and modulation order information of each stream data.

The partial linear coefficient generator 300 according to the present invention plays a role of preliminarily obtaining a linear coefficient (weight or weight matrix) using a ZF or MMSE algorithm to be used in the partial symbol detector 304.

In this case, when the ZF algorithm is used, the channel gain value, the received stream data, and the modulation order information are input. When the MMSE algorithm is used, the estimated noise variance value is an additional input.

4 is a diagram illustrating a detailed configuration of the partial linear coefficient generator 300 according to the present invention.

As shown in FIG. 4, the partial linear coefficient generator 300 may include a column matrix remover 400 and a linear weight matrix generator 402.

The column matrix removing unit 400 removes each column matrix from the channel matrix defined in Equation 1 above.

는 4x4 채널 행렬이 되며, 열행렬 제거부(400)는 각 열행렬을 제거하여 4개의 3x4 부분 행렬을 생성한다. In the present invention, since M and N are 4, the channel matrix

Becomes a 4x4 channel matrix, and the column matrix remover 400 generates four 3x4 partial matrices by removing each column matrix.

The linear weight matrix generator 402 generates a linear weight matrix using ZF or MMSE algorithm as shown in Equation 3 using the four partial matrixes generated.

This may be represented by Equation 4 below.

,,,

,,,

ZF:

MMSE:

The linear weight matrix generated in Equation 4 becomes an input value of the partial symbol detector 304, and the partial symbol detector 304 detects a transmission symbol candidate vector using the linear weight matrix.

5 is a diagram illustrating a detailed configuration of a partial symbol removing unit according to the present invention.

The partial symbol removing unit 302 according to the present invention performs a function of removing all transmittable symbols of specific stream data as shown in Equation 5 below. That is, the partial symbol remover 302 generates a first symbol vector by removing all transmittable symbols of each transmit antenna from all received data streams.

는 송신 심볼의 인덱스이며

는

변조 차수의 인덱스이다.here,

Is the index of the transmit symbol

Is

The index of the modulation order.

는 수신된 전체 데이터 스트림 중 번째 송신 안테나에서 송신 가능한 모든 심볼 중에서

Of all symbols that can be transmitted by the first transmit antenna in the entire received data stream.

번째 심볼을 제거한 심볼 벡터이다.

Symbol vector with the first symbol removed.

인 경우

개,After removing the symbol, the partial symbol removing unit 302 according to the present invention,

If

dog,

인 경우

개,

인 경우

개,

경우

개의 제1 심볼 벡터를 출력한다.

If

dog,

If

dog,

Occation

Output the first symbol vector.

6 is a diagram illustrating a detailed configuration of a partial symbol detection unit according to the present invention.

As shown in FIG. 6, the partial symbol detector according to the present invention includes a partial symbol vector generator 600 and a modulation slicer (QAM Slicer) 602, thereby generating a transmission symbol candidate vector.

The partial symbol vector generator 600 multiplies the linear weight matrix generated by the partial linear coefficient generator 300 using the ZF or MMSE algorithm and the received signal from which the symbol that can be transmitted by the partial symbol remover 302 has been removed. Generate the remaining symbols removed, i.e., the partial symbol vector (second symbol vector).

The partial symbol vector generator 600 selects a modulation slicer corresponding to the modulation order of the data stream of each transmitting antenna.

Here, the detection of the second symbol vector may be expressed by Equation 6 below.

는

번째 송신 안테나에서 송신 가능한 심볼

를 제거한 나머지 심볼 벡터(제2 심볼 벡터)의 값이다. here,

Is

Transmittable at the first transmit antenna

Is the value of the remaining symbol vectors (second symbol vectors).

가 된다.Since the total number of partial symbol vectors generated is the sum of the modulation order sizes of each transmitting antenna, the number of transmitting antennas (M) is assumed to be 4.

Becomes

를

개 생성한다.The partial symbol detector 304 adds the generated second symbol vector and the first symbol vector removed by the partial symbol remover 302 to transmit a candidate symbol vector.

To

Create a dog.

The new symbol candidate vector is shown in Equation 7 below.

7 is a diagram illustrating a detailed configuration of a square Euclidean distance calculator according to the present invention.

Referring to FIG. 7, the squared Euclidean distance calculator 306 calculates a squared Euclidean distance as shown in Equation 8 using the transmission symbol candidate vector generated by the partial symbol detector 304.

는 경판정과 연판정에 모두 사용된다. Calculated in Equation 8 Four seated Euclidean street

Is used for both hard and soft decisions.

개의 자승 유클리디언 거리

중 가장 짧은 거리 값을 갖는 송신 심볼 후보 벡터를 송신 심볼이라 판정한다.At the time of hard decision, the least square Euclidean selection unit 310 generates the following equation (9)

Four seated Euclidean street

The transmission symbol candidate vector having the shortest distance value is determined as the transmission symbol.

In the soft decision, the bit LLR generator 308 generates LLR values of all bits of the transmission symbol candidate vector and transfers them to the channel decoder 116-n.

According to the present invention, it is assumed that the channel decoder 116-n is a Viterbi decoder and a turbo decoder.

The LLR generation method uses a max-log approximation method and is generated as in Equation 10 below.

는

의 부분집합

을 이용하여

번째 송신 안테나의

번째 비트의 LLR을 생성한다. As in Equation 10,

Is

Subset of

Using

Of the first transmit antenna

Generate the LLR of the first bit.

In the case of using Equation 10, the conventional QRM-MLD and sphere decoding signal detection schemes fail to generate LLRs of all bits. In order to solve this problem, clipping techniques using a constant value or increasing the number of candidate vectors have been studied. Increasing the number of candidate vectors increases computational complexity and, in the case of the clipping technique, selects a correct clipping constant value by SNR or channel estimation error. Incorrect constant values cause significant performance degradation. In addition, in the conventional QRM-MLD and sphere decoding techniques, there is a large difference in diversity between symbols included in the candidate vector. That is, in the case of initially detected symbols, a phenomenon occurs in which one or two of a plurality of transmittable symbols are fixed to a final candidate symbol vector. Therefore, a performance difference with the last detected symbol where most of the transmittable symbols exist in the final candidate symbol vector occurs. In the case of a signal detection technique in which such a phenomenon occurs, in the MIMO system using the spatial multiplexing method described in FIG. 1, a data stream having severe performance degradation adversely affects the performance of the overall system. In addition, in the case of the multi-user system using the cooperative spatial multiplexing method described with reference to FIG. 2, a performance difference is generated between data streams of various users by a signal detection technique.

FIG. 8 is a diagram illustrating a frame error rate (FER) between stream data of various signal detection techniques.

8A shows that performance difference between data streams does not occur due to the performance of the MMSE signal detection technique. However, in the MMSE-OSIC signal detection technique of FIG. 8B and the QRM-MLD technique of FIG. 8C, there is a large difference in error performance between stream data.

8D is a diagram illustrating error performance between stream data of the present invention. Through this, it can be seen that the error performance of the present invention is similar between stream data.

The present invention can generate LLRs for every bit, using at least once every symbol that can be transmitted for multiple data streams. In addition, the performance of all data streams is similar by applying the partial symbol remover 302 once for all data streams and applying the partial symbol detector 304 to each data stream.

Therefore, there is no problem of difference in error performance between data streams generated by the existing OSIC signal detection technique, QRM-MLD technique, or sphere decoding.

FIG. 9A shows a soft decision error performance result when using a Viterbi decoder, and FIG. 9B shows a soft decision error performance result when using a turbo decoder. This result shows that the performance is improved compared to the existing suboptimal signal detection technique QRM-MLD, and the difference between the optimal performance ML search (max-log) and less than 1dB occurs.

Therefore, the signal detection technique of the present invention can be effectively applied to a multi-user system using a spatial multiplexing MIMO system and a cooperative spatial multiplexing method. In addition, even in the MIMO-OFDM system of the spatial multiplexing method, the signal can be effectively detected by applying to the subcarrier of the OFDM symbol.

Preferred embodiments of the present invention described above are disclosed for purposes of illustration, and those skilled in the art will be able to make various modifications, changes, and additions within the spirit and scope of the present invention. Additions should be considered to be within the scope of the following claims.

1 is a block diagram of a transmitting and receiving end of a general MIMO system.

2 is a block diagram of a cooperative spatial multiplexing system.

3 is a block diagram of a signal detection apparatus according to an embodiment of the present invention.

4 is a diagram illustrating a detailed configuration of a partial linear coefficient generating unit according to the present invention.

5 is a diagram illustrating a detailed configuration of a partial symbol removing unit according to the present invention.

6 is a diagram showing the detailed configuration of a partial symbol detection unit according to the present invention;

7 is a diagram showing a detailed configuration of a square Euclidean distance calculation unit according to the present invention.

8 illustrates frame error rate (FER) between stream data of various signal detection techniques.

9 illustrates error performance of soft decision signal detection according to an embodiment of the present invention.

Claims (19)

A signal detection device of a single receiver having a plurality of antennas in a system in which at least one transmitter transmits a data stream in a spatial multiplexing scheme, A partial linear coefficient generator which generates a linear weight matrix using a preset algorithm in a channel matrix formed between the transmitter and the single receiver; A partial symbol remover configured to remove all transmittable symbols of each transmit antenna from the received total data streams to generate a first symbol vector; And And a partial symbol detector configured to generate a transmission symbol candidate vector using the generated linear weight matrix and the first symbol vector. The method of claim 1, The partial linear coefficient generator, A column matrix removing unit which removes each column matrix of the channel matrix to generate M-1 partial matrices; And And a linear weight matrix generator for generating the linear weight matrix by applying the partial matrix to the preset algorithm. The method of claim 1, The partial linear coefficient generator generates a linear weight matrix using at least one of a zero forcing (ZF) algorithm and a minimum mean square error (MMSE) algorithm. The method of claim 1, The partial symbol removing unit selects a transmittable symbol of an i th transmit antenna, multiplies the selected symbol by a column matrix corresponding to the i th transmit antenna in the channel matrix, and then removes the multiplied value from the entire data stream. Detection device. The method of claim 4, wherein The partial symbol removing unit selects a number of symbols corresponding to the modulation order of the data stream by the i th transmit antenna. The method of claim 1, The partial symbol removing unit removes all transmittable symbols of each transmitting antenna according to the following equation.

Is the index of the transmit symbol

Is

Index of modulation order,

In the entire data stream

The symbol vector from which all symbols are transmitted from the first transmit antenna, with the second symbol removed. The method of claim 1, And the partial symbol detector multiplies the linear weight matrix by the first symbol vector to detect a second symbol vector corresponding to the remainder other than a symbol removed by the partial symbol remover for an i th transmit antenna. The method of claim 7, wherein The partial symbol detection unit detects a second symbol vector for each transmit antenna according to the following equation.

Is

Transmittable at the first transmit antenna

Is the remainder of the symbol vector. The method of claim 7, wherein And the partial symbol detection unit adds the first symbol vector and the second symbol vector to generate a transmission symbol candidate vector. The method of claim 7, wherein And the partial symbol detector selects a modulation slicer corresponding to a modulation order of a data stream of each transmitting antenna. The method of claim 7, wherein And a squared Euclidean distance calculator configured to perform a predetermined number of squared Euclidean distance calculations using the generated transmission symbol candidate vector. The method of claim 11, The square detection Euclidean distance calculation is performed according to the following equation.

The method of claim 11, And a minimum squared Euclidean selection unit for determining a transmission candidate symbol vector having a shortest distance value among a predetermined number of squared Euclidean distances as a transmission symbol in hard decision.

The method of claim 11, And a bit LLR generator configured to generate a Log-Likelihood Ratio (LLR) value of all bits of the transmission symbol candidate vector when the soft decision is made. The method of claim 14, The generated LLR value is transmitted to a channel decoder, wherein the channel decoder is at least one of a Viterbi decoder and a turbo decoder. The method of claim 14, And the input of the signal detection device comprises at least one of a channel gain, stream data received at each of the plurality of antennas, and an estimated noise dispersion value. The method of claim 1, And the at least one transmitter is one of a single transmitter having an antenna number M (M is a natural number of 2 or more) and a plurality of transmitters each having at least one antenna and having a total number of antennas M. A signal detection device of a single receiver having a plurality of antennas in a system in which at least one transmitter transmits a data stream in a spatial multiplexing scheme, A partial symbol eliminator for generating a symbol vector from which all transmittable symbols of each transmit antenna are removed from the entire received data stream; The partial symbol removing unit selects a transmittable symbol of an i-th transmit antenna, multiplies the selected symbol by a column matrix corresponding to the i-th transmit antenna in the channel matrix, and then removes the multiplied value from the entire data stream. Signal detection device for generating a symbol vector. A method for detecting a signal by a single receiver having a plurality of antennas in a system in which at least one transmitter transmits a data stream in a spatial multiplexing scheme, (a) generating a linear weight matrix using a predetermined algorithm in a channel matrix formed between the at least one transmitter and the single receiver; (b) generating a first symbol vector by removing all transmittable symbols of each transmit antenna from the received total data stream; (c) generating a transmission symbol candidate vector using the generated linear weight matrix and the first symbol vector; And (d) calculating a square Euclidean distance using the generated transmission symbol candidate vector.

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